sse

__m128 a; __m128 b; How to code a != b ? what to use: _mm_cmpneq_ps or _mm_cmpneq_ss ? How to process the result ? Can't find adequate docs. You should probably use _mm_cmpneq_ps . However the interpretation of comparisons is a little different with SIMD code than with scalar code. Do you want to test for any corresponding element not being equal ? Or all corresponding elements not being equal ? To test the results of the 4 comparisons from _mm_cmpneq_ps you can use _mm_movemask_epi8 . Note that comparing floating point values for equality or inequality is usually a bad idea, except in very

I want to learn about parallel programming using Intel's Haswell CPU microarchitecture. About using SIMD: SSE4.2, AVX2 in asm/C/C++/(any other langs)?. Can you recommend books, tutorials, internet resources, courses? Thanks! Z boson It sounds to me like you need to learn about parallel programming in general on the CPU. I started looking into this about 10 months ago before I ever used SSE, OpenMP, or intrinsics so let me give a brief summary of some important concepts I have learned and some useful resources. There are several parallel computing technologies that can be employed: MIMD, SIMD,

This question already has an answer here: How to sum __m256 horizontally? 2 answers I have two arrays of floats and I would like to calculate the dot product, using SSE and AVX, in the lowest latency possible. I am aware there is a 256-bit dot product intrinsic for floats but I have read on SO that this is slower than the below technique: ( https://stackoverflow.com/a/4121295/997112 ). I have done most of the work, the vector temp_sums contains all the sums, I just need to sum all the eight 32-bit sums contained within temp_sum at the end. #include "xmmintrin.h" #include "immintrin.h" int main

I have the following function: template <typename T> void SSE_vectormult(T * A, T * B, int size) { __m128d a; __m128d b; __m128d c; double A2[2], B2[2], C[2]; const double * A2ptr, * B2ptr; A2ptr = &A2[0]; B2ptr = &B2[0]; a = _mm_load_pd(A); for(int i = 0; i < size; i+=2) { std::cout << "In SSE_vectormult: i is: " << i << '\n'; A2[0] = A[i]; B2[0] = B[i]; A2[1] = A[i+1]; B2[1] = B[i+1]; std::cout << "Values from A and B written to A2 and B2\n"; a = _mm_load_pd(A2ptr); b = _mm_load_pd(B2ptr); std::cout << "Values converted to a and b\n"; c = _mm_mul_pd(a,b); _mm_store_pd(C, c); A[i] = C[0]; A[i

Is there a convention for displaying/writing large registers, like those available in the Intel AVX instruction set? For example, if you have 1 in the least significant byte, and 20 in the most significant byte, and 0 elsewhere in an xmm register, for a byte-wise display is the following preferred (little-endian): [1, 0, 0, 0, ..., 0, 20] or is this preferred: [20, 0, 0, 0, ..., 0, 1] Similarly, when displaying such registers as made up of larger data items, is the same rule applied? E.g., to display the register as DWORDs, I assume each DWORD is still written in the usual (big-endian) way,

This question already has an answer here: Is it possible to use SSE and SSE2 to make a 128-bit wide integer? 1 answer My impression is definitely not but perhaps there is a clever trick? Thanks. Not directly, but there are 64 bit arithmetic operations which can be easily combined to perform 128 bit (or greater) precision. The xmm registers can do arithmetics on 8, 16, 32 and 64 bit integers. It doesn't produce a carry flag so you can't extend the precision beyond 64 bits. The extended precision math libraries use the general purpose registers which are 32 bit or 64 bit, depending on the OS. 来源

If an SSE/AVX register's value is such that all its bytes are either 0 or 1, is there any way to efficiently get the indices of all non zero elements? For example, if xmm value is | r0=0 | r1=1 | r2=0 | r3=1 | r4=0 | r5=1 | r6=0 |...| r14=0 | r15=1 | the result should be something like (1, 3, 5, ... , 15). The result should be placed in another _m128i variable or char[16] array. If it helps, we can assume that register's value is such that all bytes are either 0 or some constant nonzero value (not necessary 1). I am pretty much wondering if there is an instruction for that or preferably C/C++

I'm writing a SSE code to 2D convolution but SSE documentation is very sparse. I'm calculating dot product with _mm_dp_ps and using _mm_extract_ps to get the dot product result, but _mm_extract_ps returns a hex that represents a float and I can't figure out how to convert this hex float to a regular float. I could use __builtin_ia32_vec_ext_v4sf that returns a float but I wanna keep compatibility with others compilers. _mm_extract_ps (__m128 __X, const int __N) { union { int i; float f; } __tmp; __tmp.f = __builtin_ia32_vec_ext_v4sf ((__v4sf)__X, __N); return __tmp.i; } What point I'm missing?